<p>Cities are key drivers of economic progress and play a decisive role in global climate action. Cities’ gross domestic product (GDP) data serves as a critical tool for evaluating economic progress and also offers a window into broader well-being, such as healthcare, education, and infrastructure. However, city-level GDP projections remain absent in China. This study uses the Cobb-Douglas production model to develop city-level GDP from 2020 to 2100, accounting for China’s unique socio-economic conditions. The dataset is validated by comparing its results with historical data and other future GDP scenarios. We develop 27 scenarios by varying technology, fertility, and intercity interaction across three levels each, considering China’s two-child/three-child policy, regional collaborative development, western development strategies, and technological advancements like AI. Among these, the Labor-Constraint Pathway and BAU Pathway closely align with the SSP1 and SSP2 scenarios, respectively. These scenarios provide a more accurate representation of future city-level GDP dynamics in China.</p>

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City-level GDP estimates for China under alternative pathways from 2020 to 2100

  • Jinjie Sun,
  • Rui Wang,
  • Jiachen Wang,
  • Shangchen Zhang,
  • Mingyu Lei,
  • Mengzhen Zhao,
  • Junming Zhu,
  • Can Wang,
  • Wenjia Cai

摘要

Cities are key drivers of economic progress and play a decisive role in global climate action. Cities’ gross domestic product (GDP) data serves as a critical tool for evaluating economic progress and also offers a window into broader well-being, such as healthcare, education, and infrastructure. However, city-level GDP projections remain absent in China. This study uses the Cobb-Douglas production model to develop city-level GDP from 2020 to 2100, accounting for China’s unique socio-economic conditions. The dataset is validated by comparing its results with historical data and other future GDP scenarios. We develop 27 scenarios by varying technology, fertility, and intercity interaction across three levels each, considering China’s two-child/three-child policy, regional collaborative development, western development strategies, and technological advancements like AI. Among these, the Labor-Constraint Pathway and BAU Pathway closely align with the SSP1 and SSP2 scenarios, respectively. These scenarios provide a more accurate representation of future city-level GDP dynamics in China.